Autoimmune disorders constitute a diverse group of phenotypes with overlapping features and a tendency toward familial aggregation. Recent data from the investigators on this proposal and others have now clearly shown that common underlying genes are involved in many of these disorders. The rationale for this proposal rests on the assumption that multiplex families with autoimmunity are enriched for multiple risk genes, and that by focusing on particular phenotypic subgroups in these families, it will be possible to more efficiently identify these genes. We will employ a comprehensive "whole genome association" approach to the discovery of such genes. The proposal builds upon a collection of multiplex autoimmune families (the MADGC collection) that has already been established by the principal investigators. In specific Aim 1 we will assemble a registry of 800 multiplex families in whom two or more members have evidence of autoimmunity. Registry and enrollment criteria will include a requirement that at least one member of these families have one of five "core" autoimmune diseases. The five core diseases will include rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), Autoimmune thyroid disease (AITD, either Graves disease or Hashimoto's thyroiditis), multiple sclerosis (MS), and type 1 diabetes (T1D). In specific Aim 2 we will carry out a genome wide screen for association using 317,000 SNPs (Illumina HapMap300). One thousand affected subjects, one member from each multiplex family, will be utilized for the gene discovery dataset and will be individually genotyped. We will study 500 subjects from each of two groups: 1) SLE with high titer autoantibodies, or 2) Hashimoto's thyroiditis with the presence of anti-thyroglobulin antibodies. Control subjects will be drawn from a unique collection of 18,000 control subjects and matched by age sex, ethnicity and ancestry informative SNP markers. In specific Aim 3 we will replicate findings on independent datasets with a view to fine mapping and definitive identification of risk alleles. These studies will lead to the identification of genes which may underlie multiple autoimmune phenotypes with a predominant humoral component. The family resources collected in specific aim 1 will also permit the future evaluation of these genetic risk factors in subjects with preclinical autoimmunity, as well as the identification of gene-environment interactions that are involved in human autoimmune disorders.